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Insufficient stability of micellar drug delivery systems is still the major limitation to their systematic application in chemotherapy. This work demonstrates novel π-electron stabilized polyelectrolyte block copolymer micelles based on dendritic polyglycerolsulfate-cystamine-block-poly(4-benzoyl-1,4-oxazepan-7-one)-pyrene (dPGS-SS-POxPPh-Py) presenting a very low critical micelle concentration (CMC) of 0.3 mg L−1 (18 nM), 55-fold lower than that of conventional amphiphilic block copolymer micelles. The drug loading capacities of up to 13 wt% allow the efficient encapsulation of the chemotherapeutic Docetaxel (DTX). The spherical morphology of the micelles was proven by cryogenic electron microscopy (cryo-EM). Gaussian Analysis revealed well-defined sizes of 57 nm and 80 nm in the unloaded/loaded state, respectively. Experiments by dynamic light scattering (DLS), ultraviolet-visible spectroscopy (UV-VIS), fluorescence spectroscopy, and cross-polarization solid-state 13C NMR studied the π–π interactions between the core-forming block segment of dPGS-SS-POxPPh-Py and DTX. The findings point to a substantial contribution of these noncovalent interactions to the system's high stability. By confocal laser scanning microscopy (CLSM), the cellular uptake of fluorescein-labelled FITC-dPGS-SS-POxPPh-Py micelles was monitored after one day displaying the successful cell insertion of the cargo-loaded systems. To ensure the drug release in cancerous cells, the disassembly of the micellar DTX-formulations was achieved by reductive and enzymatic degradation studied by light scattering and GPC experiments. Further, no size increase nor disassembly in the presence of human serum proteins after four days was detected. The precise in vitro drug release was also given by the high potency of inhibiting cancer cell growth, finding half-maximal inhibitory concentrations (IC50) efficiently reduced to 68 nM coming along with high viabilities of the empty polymer materials tested on tumor-derived HeLa, A549, and McF-7 cell lines after two days. This study highlights the substantial potential of micelles tailored through the combination of π-electron stabilization with dendritic polyglycerolsulfate for targeted drug delivery systems, enabling them to have a significant foothold in the clinical treatment of cancer.

Exenatide is a small therapeutic peptide being currently used in clinic for the treatment of diabetes mellitus type II, however, displaying a short blood circulation time which makes two daily injections necessary. Covalent polymer modification of a protein is a well-known approach to overcome this limitation, resulting in steric shielding, an increased size and therefore a longer circulation half-life. In this study, we employed site-selective C-terminal polymer ligation of exenatide via copper-catalyzed azide-alkyne-cycloaddition (CuAAC) to yield 1:1-conjugates of either poly(ethylene glycol) (PEG) or linear polyglycerol (LPG) of different molecular weights. Our goal was to compare the impact of the two polymers on size, structure and activity of exenatide on the in vitro and in vivo level. Both polymers did not alter the secondary structure of exenatide and expectedly increased its hydrodynamic size, where the LPG-versions of exenatide showed slightly smaller values than their PEG-analogs of same molecular weight. Upon conjugation, GLP-1 receptor activation was diminished, however, still enabled maximum receptor response at slightly higher concentrations. Exenatide modified with a 40 kDa LPG (Ex-40-LPG) showed significant reduction of the blood glucose level in diabetic mice for up to 72 h, which was comparable to its PEG-analog, but 9-fold longer than native exenatide (8 h).

In this paper, we present well-defined dPGS-SS-PCL/PLGA/PLA micellar systems demonstrating excellent capabilities as a drug delivery platform in light of high stability and precise in vitro and in vivo drug release combined with active targetability to tumors. These six amphiphilic block copolymers were each targeted in two different molecular weights (8 or 16 kDa) and characterized using 1H NMR, gel permeation chromatography (GPC), and elemental analysis. The block copolymer micelles showed monodispersed size distributions of 81-187 nm, strong negative charges between -52 and -41 mV, and low critical micelle concentrations (CMCs) of up to 1.13-3.58 mg/L (134-527 nM). The serum stability was determined as 94% after 24 h. The drug-loading efficiency for Sunitinib ranges from 38 to 83% (8-17 wt %). The release was selectively triggered by glutathione (GSH) and lipase, reaching 85% after 5 days, while only 20% leaching was observed under physiological conditions. Both the in vitro and in vivo studies showed sustained release of Sunitinib over 1 week. CCK-8 assays on HeLa lines demonstrated the high cell compatibility (1 mg/mL, 94% cell viability, 48 h) and the high cancer cell toxicity of Sunitinib-loaded micelles (IC50 2.5 μg/mL). By in vivo fluorescence imaging studies on HT-29 tumor-bearing mice, the targetability of dPGS7.8-SS-PCL7.8 enabled substantial accumulation in tumor tissue compared to nonsulfated dPG3.9-SS-PCL7.8. As a proof of concept, Sunitinib-loaded dPGS-SS-poly(ester) micelles improved the antitumor efficacy of the chemotherapeutic. A tenfold lower dosage of loaded Sunitinib led to an even higher tumor growth inhibition compared to the free drug, as demonstrated in a HeLa human cervical tumor-bearing mice model. No toxicity for the organism was observed, confirming the good biocompatibility of the system.

Neuregulin-1 (NRG1) represents an important factor for multiple processes including neurodevelopment, brain functioning or cognitive functions. Evidence from animal research suggests an effect of NRG1 on the excitation-inhibition (E/I) balance in cortical circuits. However, direct evidence for the importance of NRG1 in E/I balance in humans is still lacking. In this work, we demonstrate the application of computational, biophysical network models to advance our understanding of the interaction between cortical activity observed in neuroimaging and the underlying neurobiology. We employed a biophysical neuronal model to simulate large-scale brain dynamics and to investigate the role of polymorphisms in the NRG1 gene (rs35753505, rs3924999) in n = 96 healthy adults. Our results show that G/G-carriers (rs3924999) exhibit a significant difference in global coupling (P = 0.048) and multiple parameters determining E/I-balance such as excitatory synaptic coupling (P = 0.047), local excitatory recurrence (P = 0.032) and inhibitory synaptic coupling (P = 0.028). This indicates that NRG1 may be related to excitatory recurrence or excitatory synaptic coupling potentially resulting in altered E/I-balance. Moreover, we suggest that computational modeling is a suitable tool to investigate specific biological mechanisms in health and disease.

Poor water solubility and low bioavailability of active pharmaceutical ingredients (APIs) are major causes of friction in the pharmaceutical industry and represent a formidable hurdle for pharmaceutical drug development. Drug delivery remains the major challenge for the application of new small-molecule drugs as well as biopharmaceuticals. The three challenges for synthetic delivery systems are: (i) controlling drug distribution and clearance in the blood; (ii) solubilizing poorly water-soluble agents, and (iii) selectively targeting specific tissues. Although several polymer-based systems have addressed the first two demands and have been translated into clinical practice, no targeted synthetic drug delivery system has reached the market. This Review is designed to provide a background on the challenges and requirements for the design and translation of new polymer-based delivery systems. This report will focus on chemical approaches to drug delivery for systemic applications.

Inflammation plays an important role in the response to danger signals arising from damage to our body and in restoring homeostasis. Dysregulated inflammatory responses occur in many diseases, including cancer, sepsis and autoimmunity. The efficacy of anti-inflammatory drugs, developed for the treatment of dysregulated inflammation, can be potentiated using biomaterials, by improving the bioavailability of drugs and by reducing side effects. In this Review, we first outline key elements and stages of the inflammatory environment and then discuss the design of biomaterials for different anti-inflammatory therapeutic strategies. Biomaterials can be engineered to scavenge danger signals, such as reactive oxygen and nitrogen species and cell-free DNA, in the early stages of inflammation. Materials can also be designed to prevent adhesive interactions of leukocytes and endothelial cells that initiate inflammatory responses. Furthermore, nanoscale platforms can deliver anti-inflammatory agents to inflammation sites. We conclude by discussing the challenges and opportunities for biomaterial innovations in addressing inflammation.

EEG and fMRI are thought to measure partly distinct, partly overlapping, and certainly incomplete aspects of neuronal activity. Brain network models (BNMs) are used to simulate neuronal activity, like the dynamics of postsynaptic potentials, or spike-firing activity, and may conjointly predict both, EEG and fMRI, and therefore allow for the integration and the analysis of the two signals. The usual motivation for EEG–fMRI integration is to use both techniques in a complementary fashion by combining their strengths, while ameliorating their weaknesses. For instance, EEG measures electric activity on the scalp with a high temporal sampling rate, but a low spatial resolution (e.g., due to volume conduction effects). On the other hand, fMRI BOLD contrast is an indirect (proxy) measure of neural activity that is sensitive for the fluctuation of blood oxygenation at a relatively low temporal resolution. Some of the appeal of brain simulation-based integration of EEG–fMRI data is related to the idea that after fitting a neural model to reproduce observed activity, the internal activity of the model can tell us something about unobservable activity, like neural firing, which can only be measured invasively and in a spatially restricted manner. Brain simulation-based approaches have the potential to not only integrate EEG and fMRI, but basically data from every modality that can either directly (like multi-electrode recordings) or indirectly (like fMRI) be linked with the neural model.

1.AbstractBrain Network Models (BNMs) are a family of dynamical systems that simulate whole brain activity using neural mass models to represent local activity in different brain regions that influence each other via a global structural network. Research has been interested in using these network models to explain measured whole brain activity measured via resting state functional magnetic resonance imaging (rs-fMRI). Properties computed over longer periods of simulated and measured data such as average functional connectivity (FC), have shown to be comparable with similar properties estimated from measured rs-fMRI data. While this shows that these network models have similar properties over the dynamical landscape, it is unclear how well simulated trajectories compare with empirical trajectories on a timepoint-by-timepoint basis. Previous studies have shown that BNMs are able to produce relevant features at shorter timescales, but analysis of short-term trajectories or transient dynamics as defined by synchronized predictions from BNM made at the same timescale as the collected data has not yet been conducted. Relevant neural processes exist in the time frame of measurements and are often used in task fMRI studies to understand neural responses to behavioral cues. Therefore, it is important to investigate how much of these dynamics are captured by our current brain simulations. To test the nature of BNMs short term trajectories against observed data, we utilize a deep learning technique known as Neural ODE that based on an observed sequence of fMRI measurements, estimates the initial conditions such that the BNM’s simulation is synchronized to produce the closest trajectory relative to the observed data. We test to see if the parameterization of a specific well studied BNM, the Firing Rate Model, calculated by maximizing its accuracy in reproducing observed short term trajectories matches with the parameterized model that produces the best average long-term metrics. Our results show that such an agreement between parameterization using long and short simulation analysis exists if also considering other factors such as the sensitivity in accuracy with relative to changes in structural connectivity. Therefore, we conclude that there is evidence that by solving for initial conditions, BNMs can be simulated in a meaningful way when comparing against measured data trajectories, although future studies are necessary to establish how BNM activity relate to behavioral variables or to faster neural processes during this time period.

Targeted delivery and extended blood circulation of anticancer drugs have been the challenges for decreasing the adverse side effects and improving the therapeutic efficiency in cancer chemotherapy. Herein, we present a drug delivery system (DDS) based on biodegradable dendritic polyglycerol sulfate-bearing poly(caprolactone) (dPGS-PCL) chains, which has been synthesized on 20 g scale using a straightforward two-step protocol. In vivo fluorescence imaging demonstrated a significant accumulation of the DDS in the tumor environment. Sunitinib, an anticancer drug, was loaded into the DDS and the drug-induced toxicity was investigated in vitro and in vivo. The drug encapsulated in dPGS-PCL and the free drug showed similar toxicities in A431 and HT-29 cells, and the cellular uptake was comparable. The straightforward and large-scale synthesis, the organic solvent-free drug-loading approach, together with the tumor targetability of the biodegradable dendritic polyglycerols, render this copolymer a promising candidate for targeted cancer nanomedicine drug delivery systems.

Since several decades, PEGylation is known to be the clinical standard to enhance pharmacokinetics of biotherapeutics. In this study, we introduce polyglycerol (PG) of different lengths and architectures (linear and hyperbranched) as an alternative polymer platform to poly(ethylene glycol) (PEG) for half-life extension (HLE). We designed site-selective N-terminally modified PG-protein conjugates of the therapeutic protein anakinra (IL-1ra, Kineret) and compared them systematically with PEG analogues of similar molecular weights. Linear PG and PEG conjugates showed comparable hydrodynamic sizes and retained their secondary structure, whereas binding affinity to IL-1 receptor 1 decreased with increasing polymer length, yet remained in the low nanomolar range for all conjugates. The terminal half-life of a 40 kDa linear PG-modified anakinra was extended 4-fold compared to the unmodified protein, close to its PEG analogue. Our results demonstrate similar performances of PEG- and PG-anakinra conjugates and therefore highlight the outstanding potential of polyglycerol as a PEG alternative for half-life extension of biotherapeutics.

Structural connectivity (SC), the physical pathways connecting regions in the brain, and functional connectivity (FC), the temporal coactivations, are known to be tightly linked. However, the nature of this relationship is still not understood. In the present study, we examined this relation more closely in six separate human neuroimaging datasets with different acquisition and preprocessing methods. We show that using simple linear associations, the relation between an individual’s SC and FC is not subject specific for five of the datasets. Subject specificity of SC-FC fit is achieved only for one of the six datasets, the multimodal Glasser Human Connectome Project (HCP) parcellated dataset. We show that subject specificity of SC-FC correspondence is limited across datasets due to relatively small variability between subjects in SC compared with the larger variability in FC., Author Summary We present evidence that, in most standard datasets, the subject variation in structural connectivity (SC) may be too weak to be reflected in the functional connectivity (FC) variability. However, subject specificity of SC-FC can be captured via fine, multimodally parcellated data because of greater SC variability across subjects. Nonetheless, SC and FC each show a large component that is common across subjects, which sets limitations on the extent of SC-FC subject specificity. Implications of these findings for personalized medicine should be considered. Namely, attention to the quality of processing and parcellation methods is critical for furthering our understanding of the relationship between individual SC and FC.

Models of large-scale brain networks that are informed by the underlying anatomical connectivity contribute to our understanding of the mapping between the structure of the brain and its dynamical function. Connectome-based modelling is a promising approach to a more comprehensive understanding of brain function across spatial and temporal scales, but it must be constrained by multi-scale empirical data from animal models. Here we describe the construction of a macaque (Macaca mulatta and Macaca fascicularis) connectome for whole-cortex simulations in TheVirtualBrain, an open-source simulation platform. We take advantage of available axonal tract-tracing datasets and enhance the existing connectome data using diffusion-based tractography in macaques. We illustrate the utility of the connectome as an extension of TheVirtualBrain by simulating resting-state BOLD-fMRI data and fitting it to empirical resting-state data., Design Type(s)data integration objective • source-based data transformation objective • modeling and simulation objectiveMeasurement Type(s)brain measurementTechnology Type(s)functional magnetic resonance imaging • Diffusion Weighted ImagingFactor Type(s)Sample Characteristic(s)Macaca • brain Machine-accessible metadata file describing the reported data (ISA-Tab format)

Functional interactions in the brain are constrained by the underlying anatomical architecture, and structural and functional networks share network features such as modularity. Accordingly, age-related changes of structural connectivity (SC) may be paralleled by changes in functional connectivity (FC). We provide a detailed qualitative and quantitative characterization of the SC-FC coupling in human aging as inferred from resting-state blood oxygen-level dependent functional magnetic resonance imaging and diffusion-weighted imaging in a sample of 47 adults with an age range of 18-82. We revealed that SC and FC decrease with age across most parts of the brain and there is a distinct age-dependency of regionwise SC-FC coupling and network-level SC-FC relations. A specific pattern of SC-FC coupling predicts age more reliably than does regionwise SC or FC alone (r = 0.73, 95% CI = [0.7093, 0.8522]). Hence, our data propose that regionwise SC-FC coupling can be used to characterize brain changes in aging. Hum Brain Mapp 37:2645-2661, 2016. © 2016 Wiley Periodicals, Inc.

Structural connectivity (SC), the physical pathways connecting regions in the brain, and functional connectivity (FC), the temporal co-activations, are known to be tightly linked. However, the nature of this relationship is still not understood. In the present study, we examined this relation more closely in six separate human neuroimaging datasets with different acquisition and preprocessing methods. We show that using simple linear associations, the relation between an individual’s SC and FC is not subject-specific for five of the datasets. Subject-specificity of SC-FC fit is achieved only for one of the six datasets, the multi-modal Glasser HCP parcellated dataset. We show that subject-specificity of SC-FC correspondence is limited across datasets due to relatively small variability between subjects in SC compared to the larger variability in FC.

Alzheimer's disease (AD) is marked by cognitive dysfunction emerging from neuropathological processes impacting brain function. AD affects brain dynamics at the local level, such as changes in the balance of inhibitory and excitatory neuronal populations, as well as long-range changes to the global network. Individual differences in these changes as they relate to behaviour are poorly understood. Here, we use a multi-scale neurophysiological model, “The Virtual Brain (TVB)”, based on empirical multi-modal neuroimaging data, to study how local and global dynamics correlate with individual differences in cognition. In particular, we modeled individual resting-state functional activity of 124 individuals across the behavioural spectrum from healthy aging, to amnesic Mild Cognitive Impairment (MCI), to AD. The model parameters required to accurately simulate empirical functional brain imaging data correlated significantly with cognition, and exceeded the predictive capacity of empirical connectomes., Highlights • Modeled local and global dynamics correlate with individual cognition in Alzheimer's. • Proof of concept of The Virtual Brain to characterize individual dynamics • Brain-behaviour relations depend on the network modeled (whole brain or limbic). • Model parameters predict cognition better than metrics of neuroimaging data.

Brain dynamics span multiple spatial and temporal scales, from fast spiking neurons to slow fluctuations over distributed areas. No single experimental method links data across scales. Here, we bridge this gap using The Virtual Brain connectome-based modelling platform to integrate multimodal data with biophysical models and support neurophysiological inference. Simulated cell populations were linked with subject-specific white-matter connectivity estimates and driven by electroencephalography-derived electric source activity. The models were fit to subject-specific resting-state functional magnetic resonance imaging data, and overfitting was excluded using 5-fold cross-validation. Further evaluation of the models show how balancing excitation with feedback inhibition generates an inverse relationship between α-rhythms and population firing on a faster time scale and resting-state network oscillations on a slower time scale. Lastly, large-scale interactions in the model lead to the emergence of scale-free power-law spectra. Our novel findings underscore the integrative role for computational modelling to complement empirical studies.

Background Indocyanine green (ICG)-enhanced fluorescence optical imaging (FOI) is an established technology for imaging of inflammation in animal models. In experimental models of arthritis, FOI findings corresponded to histologically proven synovitis. This is the first comparative study of FOI with other imaging modalities in humans with arthritis. Methods 252 FOI examinations (Xiralite system, mivenion GmbH, Berlin, Germany; ICG bolus of 0.1 mg/kg/body weight, sequence of 360 images, one image per second) were compared with clinical examination (CE), ultrasonography (US) and MRI of patients with arthritis of the hands. Results In an FOI sequence, three phases could be distinguished (P1–P3). With MRI as reference, FOI had a sensitivity of 76% and a specificity of 54%, while the specificity of phase 1 was 94%. FOI had agreement rates up to 88% versus CE, 64% versus greyscale US, 88% versus power Doppler US and 83% versus MRI, depending on the compared phase and parameter. FOI showed a higher rate of positive results compared to CE, US and MRI. In individual patients, FOI correlated significantly (p

Adhesive interactions of leukocytes and endothelial cells initiate leukocyte migration to inflamed tissue and are important for immune surveillance. Acute and chronic inflammatory diseases show a dysregulated immune response and result in a massive efflux of leukocytes that contributes to further tissue damage. Therefore, targeting leukocyte trafficking may provide a potent form of anti-inflammatory therapy. Leukocyte migration is initiated by interactions of the cell adhesion molecules E-, L-, and P-selectin and their corresponding carbohydrate ligands. Compounds that efficiently address these interactions are therefore of high therapeutic interest. Based on this rationale we investigated synthetic dendritic polyglycerol sulfates (dPGS) as macromolecular inhibitors that operate via a multivalent binding mechanism mimicking naturally occurring ligands. dPGS inhibited both leukocytic L-selectin and endothelial P-selectin with high efficacy. Size and degree of sulfation of the polymer core determined selectin binding affinity. Administration of dPGS in a contact dermatitis mouse model dampened leukocyte extravasation as effectively as glucocorticoids did and edema formation was significantly reduced. In addition, dPGS interacted with the complement factors C3 and C5 as was shown in vitro and reduced C5a levels in a mouse model of complement activation. Thus, dPGS represent an innovative class of a fully synthetic polymer therapeutics that may be used for the treatment of inflammatory diseases.

Impairment of the blood-brain barrier (BBB) after cerebral ischemia leads to extravasation of plasma constituents into the brain parenchyma. We describe a novel method using non-invasive near-infrared fluorescence (NIRF) imaging and bovine serum albumin labeled with a NIRF dye (NIRF-BSA) to detect BBB impairment after middle cerebral artery occlusion (MCAO) in mice. We first explored the time course of BBB impairment after transient MCAO using Evans blue (EB), which binds to plasma albumin in vivo. An initial BBB impairment was observed at 4-8h and a second impairment at 12-16h after reperfusion. No EB extravasation was detected at 8-12h. Non-invasive NIRF imaging with NIRF-BSA confirmed biphasic BBB impairment. Upon co-injection of NIRF-BSA with EB we found a strong correlation between the detected NIRF signal and the amount of extravasated EB (r=0.857, P=0.00178). When MCAO mice received NIRF-BSA together with gadolinium-diethylene triamine penta-acetic acid (Gd-DTPA), T1-weighted images showed Gd-DTPA enhancement at all times while NIRF imaging showed biphasic BBB impairment. In conclusion, NIRF-BSA is a suitable marker of plasma albumin extravasation in the mouse brain. Non-invasive NIRF imaging with NIRF-BSA is a useful tool to study BBB integrity in preclinical models of central nervous system pathology.

It has been shown that ED-B fibronectin (ED-B) is a potential target for plaque imaging. The aim of this study was to test a novel modified single chain anti-ED-B antibody (scFv) conjugated for near infrared fluorescence imaging (NIRF) with tetrasulfonated carbocyanine-maleimide (TSC-scFv) and to examine the association of ED-B with the presence of macrophages in a murine model of atherosclerosis. Expression of ED-B was observed in plaque areas in apolipoprotein E-deficient (apoE(-/-)) mice which increased with age and plaque load. Robust imaging was possible after explantation of the aorta and demonstrated a strong NIRF signal intensity in focal aortic and brachiocephalic plaque lesions, whereas no signals were found in undiseased areas. Plaque lesion ED-B was expressed by smooth muscle cell and was closely associated to macrophage infiltrates. Although not expressed by the same cell type, there was a significant correlation (p0.01) between ED-B and macrophage immunoreactivity. In vitro human coronary and mouse smooth muscle cells significantly increased ED-B expression after angiotensin II and TNF-alpha treatment. This study demonstrates that plaque NIRF imaging is feasible with a novel single chain antibody and that ED-B expression is closely associated with inflammation in experimental atherosclerosis.

International audience; Recent efforts to model human brain activity on the scale of the whole brain rest on connectivity estimates of large-scale networks derived from diffusion magnetic resonance imaging (dMRI). This type of connectivity describes white matter fiber tracts. The number of short-range cortico-cortical white-matter connections is, however, underrepresented in such large-scale brain models. It is still unclear on the one hand, which scale of representation of white matter fibers is optimal to describe brain activity on a large-scale such as recorded with magneto-or electroencephalography (M/EEG) or functional magnetic resonance imaging (fMRI), and on the other hand, to which extent short-range connections that are typically local should be taken into account. In this article we quantified the effect of connectivity upon large-scale brain network dynamics by (i) systematically varying the number of brain regions before computing the connectivity matrix, and by (ii) adding generic short-range connections. We used dMRI data from the Human Connec-tome Project. We developed a suite of preprocessing modules called SCRIPTS to prepare these imaging data for The Virtual Brain, a neuroinformatics platform for large-scale brain modeling and simulations. We performed simulations under different connectivity conditions and quantified the spatiotemporal dynamics in terms of Shannon Entropy, dwell time and Principal Component Analysis. For the reconstructed connectivity, our results show that the major white matter fiber bundles play an important role in shaping slow dynamics in large-scale brain networks (e.g. in fMRI). Faster dynamics such as gamma oscillations (around 40 Hz) are sensitive to the short-range connectivity if transmission delays are considered. (C) 2016 Elsevier Inc. All rights reserved.

The aim of the study is to evaluate in vivo fluorescence imaging of experimental inflammatory joint disease by applying two different near-infrared (NIR) dyes in a model of Borrelia-induced Lyme arthritis.Forty mice, 20 with Lyme arthritis and 20 controls, were examined. Two nonspecific NIR carbocyanine dyes, indocyanine green (ICG) and a hydrophilic carbocyanine derivative (1,1'-bis-[4-sulfobutyl] indotricarbocyanine-5,5'-dicarboxylic acid diglucamide monosodium salt [SIDAG]), were administered intravenously at two doses. Fluorescence images were acquired before and during 120 seconds after injection of cyanine dyes. For both dyes, the area under the curve (AUC) was determined for the interval between 40 and 80 seconds after injection. In addition, the slope of the signal decrease was compared among animal groups. Results were compared with histological findings.The general temporal fluorescence intensity course for ICG was characterized by a rapid increase, with a peak at 40-50 seconds followed by a decrease; conversely for SIDAG, by a slow increase. AUC analysis for both dyes showed that the fluorescence signal differed significantly between controls and arthritic animals (P.05). Within these groups, there were significant differences between the two doses investigated. ICG differed significantly between control and arthritic animals in the slope of the signal decrease for both doses investigated (P.05). Histological examination showed early stages of inflammation in arthritic animals.NIR fluorescence imaging based on the pharmacokinetic behavior of ICG or SIDAG is a promising approach to detect inflammatory joint changes of experimental arthritis. Moreover, SIDAG is suited to differentiate inflammatory and noninflammatory joints 24 hours after dye application.

To evaluate the feasibility of gene delivery mediated with diagnostic ultrasound and plasmid DNA (pDNA) encapsulated in gas-filled microparticles (GFMP) in rodent tumor models.This study was performed according to a protocol approved by the regional animal research committee. The model plasmid UT651 (pUT651) that contained the Escherichia coli LacZ gene for beta-galactosidase was used to demonstrate the feasibility of ultrasound-mediated gene delivery in CC531 liver tumors in rats. In preliminary experiments, a single injection of pUT651-containing GFMP was administered intraarterially (n=4) or intravenously (n=6) with simultaneous sonication (color Doppler mode, maximum mechanical index) of the GFMP passing through the capillaries of the tumors. All animals were sacrificed 2-5 days later, and liver tumors were examined for beta-galactosidase expression histochemically. Subsequently, potential medical usefulness of this delivery system was tested in nude mice bearing Capan-1 tumors (adenocarcinoma of the human pancreas) by using the plasmid RC/CMV-p16 (pRC/CMV-p16), which contains tumor suppressor gene p16. The tumor suppressor gene p16 is deleted in Capan-1 cells. Twenty-five tumor-bearing mice were classified into five groups (four to six mice per group, one treatment group, four control groups) at random. All mice were treated once weekly for 5 weeks with intravenous infusion of p16-containing GFMP or control substances with simultaneous tumor sonication with color Doppler mode ultrasound and maximum mechanical index or without ultrasound treatment. The therapeutic effect of p16 was measured as an increase in tumor volume doubling time. Data were analyzed with analysis of variance. Results were considered significant at the 5% critical level (P.05).A clear expression of pDNA was found in tumors in rats treated with a combination of pUT651-containing GFMP and ultrasound; relevant controls showed a significantly lower expression of marker gene. The controlled ultrasound-triggered release of pRC/CMV-p16 from GFMP leads to a strong tumor growth inhibition, which is significant (P.002), compared with that in controls.A combination of GFMP and ultrasound provides an effective approach for nonviral gene therapy-based cancer treatment.

To develop an in vitro assay for studying the feasibility of specific targeting of ultrasound contrast agents (USCAs) for ultrasound diagnostics by employing the parallel plate flow chamber, which provides an environment that mimics some aspects of the in vivo conditions like shear rate and flow effects.USCAs based on air-filled microparticles (MP) were functionalized with specific antibodies using carbodiimide coupling chemistry and characterized by fluorescence activated cell sorter (FACS). The binding experiments were done by subjecting the MP to shear stress as they interact with the target-coated surface of the flow chamber.A successive modification of MP with antibody and the glass surface with antigen was achieved and quantified. The binding studies showed specific attachment of targeted MP to EDB-FN (EDB domain of fibronectin) surface. The binding of MP via nonspecific interactions was minimal. The binding efficiency of antibody-loaded MP is dependent on the applied shear stress. An increase in the wall shear stress resulted in a decrease in binding efficiency. Binding efficiency was found to be correlated with the antibody density and antigen density on the interacting surfaces.The results indicate that the test system developed is reliable for characterizing targeted MP without any additional labeling and can be used as a functionality assay for studying the binding characteristic of USCA with respect to different parameters like density of targeting antibodies on the microparticle surface and of target protein. In addition, the microparticles can be studied in detail under different shear rates and flow conditions. Further studies concerning the in vitro-in vivo correlation will be necessary to further increase the value of this in vitro method.

To evaluate the feasibility of using intravenously administered L-selectin ligand-specific polymer-stabilized air-filled microparticles (MPs) for active targeting of peripheral lymph nodes under normal conditions in animal models.L-selectin ligand-specific MPs and two control substances (immunoglobulin M-isotype MPs and native MPs) were each administered in three conscious mice as a single intravenous bolus injection (1.4 x 10(7) MPs/kg). All mice were sacrificed 30 minutes after administration. Lymph nodes (cervical, inguinal, axillary, popliteal, mesenteric), spleen (positive control), and kidney (blood pool control) were removed and examined for MP-related stimulated acoustic emission (SAE) signals by using harmonic color Doppler ultrasonography (US) in a tank containing degassed water. A second experiment was performed in six anesthetized beagle dogs by using the same MP formulation. Each of the MP formulations was administered in two anesthetized dogs as a single intravenous bolus injection (1 x 10(7) MPs/kg). The popliteal lymph nodes, spleen (positive control), and kidney (blood pool control) were examined in vivo with US for MP-related SAE signals 30 minutes after administration. Fisher exact test for the one-side alternative was used for mouse data analysis.The lymph nodes of all mice (P =.05) and the popliteal lymph nodes of both dogs treated with L-selectin ligand-specific MPs showed clear MP-related SAE signals, whereas the lymph nodes of all mice and the popliteal lymph nodes of four dogs that received the control substances did not show any SAE signals.Use of an intravenously administered L-selectin ligand-specific US contrast agent is feasible for active lymph node targeting in mice and dogs.